Why most economists could not predict the rupee crash

Economists and analysts have turned bearish on the future of the rupee, over the last couple of months. But very few of them predicted the crash of the rupee.

Vivek Kaul August 27, 2013 12:37:29 IST
Why most economists could not predict the rupee crash

Economists and analysts have turned bearish on the future of the rupee, over the last couple of months. But very few of them predicted the crash of the rupee. Among the few who did were, SS Tarapore, a former deputy governor of the Reserve Bank of India, and Rajeev Malik of CLSA.

Tarapore felt that the rupee should be closer to 70 to a dollar. As he pointed out in a column published in The Hindu Business Line on January 24, 2013: "With the inflation rate persistently above that in the major industrial countries, the rupee is clearly overvalued. Adjusting for inflation rate differentials, the present nominal dollar-rupee rate of around $1 = Rs 54 should be closer to $1 = Rs 70. But our macho spirits want an appreciation of the rupee which goes against fundamentals."

Rajeev Malik of CLSA said something along similar lines in a column published on Firstpost on January 31, 2013. "The worsening current account deficit is partly signalling that the rupee is overvalued. But the RBI and everyone else are missing that clue," he wrote. The current account deficit is the difference between total value of imports and the sum of the total value of its exports and net foreign remittances.

Why most economists could not predict the rupee crash

SS Tarapore felt that the rupee should be closer to 70 to a dollar. AFP

What Tarapore and Malik said towards the end of January turned out to be true towards the end of May. The rupee was overvalued and has depreciated 20% against the dollar since then. The question is why did most economists and analysts not see the rupee crash coming, when there was enough evidence available pointing to the same?

One possible explanation lies in what Nassim Nicholas Taleb calls the turkey problem (something I have talked about in a slightly different context earlier). As Taleb writes in his latest book Anti Fragile "A turkey is fed for a thousand days by a butcher; every day confirms to its staff of analysts that butchers love turkeys "with increased statistical confidence." The butcher will keep feeding the turkey until a few days before thanksgiving. Then comes that day when it is really not a very good idea to be a turkey. So, with the butcher surprising it, the turkey will have a revision of belief-right when its confidence in the statement that the butcher loves turkeys is maximal ... the key here is such a surprise will be a Black Swan event; but just for the turkey, not for the butcher."

The Indian rupee moved in the range of 53.8-55.7 to a dollar between November 2012 and end of May 2013. This would have led the 'economists' to believe that the rupee would continue to remain stable against the dollar. The logic here was that rupee will be stable against the dollars in the days to come, because it had been stable against the dollar in the recent past.

While this is a possible explanation, there is a slight problem with it. It tends to assume that economists and analysts are a tad dumb, which they clearly are not. There is a little more to it. Economists and analysts essentially feel safe in a herd. As Adam Smith, the man referred to as the father of economics, once asserted, "Emulation is the most pervasive of human drives".

An economist or an analyst may have figured out that the rupee would crash in the time to come, but he just wouldn't know when. And given that he would be risking his reputation by suggesting the obvious. As John Maynard Keynes once wrote "Worldly wisdom teaches us that it's better for reputation to fail conventionally than succeed unconventionally".

An economist/analyst predicting the rupee crash at the beginning of the year would have been proven wrong for almost 6 months, till he was finally proven right. This is a precarious situation to be in, which economists/analysts like to avoid. Hence, they tend to go with what everyone else is predicting at a particular point of time.

Research has shown this very clearly. As Mark Buchanan writes in Forecast - What Physics, Meteorology and the Natural Sciences Can Teach Us About Economics "Financial analysts may claim to be weighing information independently when making forecasts of things like inflation...but a study in 2004 found that what analysts' forecasts actually follow most closely is other analysts' forecasts. There's a strong herding behaviour that makes the analysts' forecasts much closer to one another than they are to the actual outcomes."

And that explains to a large extent why most economists turned bearish on the rupee, after it crashed against the dollar. They were just following their herd.

There is another possible explanation for economists and analysts missing the rupee crash. As Dylan Grice, formerly an analyst with Societe Generale, and now the editor of the Edelweiss Journal, put it in a report titled What's the point of the macro? dated June 15, 2010 "Perhaps a more important thought is that we're simply not hardwired to see and act upon big moves that are predictable."

A generation of economists has grown up studying and believing in the efficient market hypothesis. It basically states that financial markets are largely efficient,meaning that at any point of time they have taken into account all the information that is available. Hence, the markets are believed to be in a state of equilibrium and they move only once new information comes in. As Buchanan writes "the efficient market theory doesn't just claim that information should move markets. It claims that only information moves markets. Prices should always remain close to their so called fundamental values - the realistic value based on accurate consideration of all information concerning the long-term prospects."

What does this mean in the context of the rupee before it crashed? At 55 to a dollar it was rightly priced and had incorporated all the information from inflation to current account deficit, into its price. And given this, there was no chance of a crash or what economists and analysts like to call big outlier moves.

Benoit Mandlebrot, a mathematician who spent considerable time studying finance, distinguished between uncertainty that is mild and that which is wild. Dylan Grice explains these uncertainties through two different examples.

As he writes "Imagine taking 1000 men at random and calculating the sample's average height. Now suppose we add the heaviest man we can find to the sample. Even if he weighed 600kg - which would make him the heaviest man in the world - he'd hardly change the estimated average. If the sample average weight was similar to the American average of 86kg, the addition of the heaviest man in the world (probably the heaviest ever) would only increase the average to 86.5 kg."

This is mild uncertainty.

Then there is wild uncertainty, which Dylan Grice explains through the following example. "For example, suppose instead of taking the weight of our 1000 American men, we took their wealth. And now, instead of adding the heaviest man in the world we took one of the wealthiest, Bill Gates. Since he'd represent around 99.9% of all the wealth in the room he'd be massively distorting the measured average so profoundly that our estimates of the population's mean and standard deviation would be meaningless...If weight was wildly distributed, a person would have to weight 30,000,000kg to have a similar effect," writes Grice.

Financial markets are wildly random and not mildly random, like economists like to believe. This means that financial markets can have big crashes. But given the belief that economists have in the efficient market hypothesis, most of them can't see any crash coming.

In fact, when it comes to worst case predictions it is best to remember a story that Howard Marks writes about in his book The Most Important Thing (and which Dylan Grice reproduced in his report titled Turning "Minimum Bullish" On Eurozone Equities dated September 8,2011). As Marks writes "We hear a lot about "worst case" projections, but they often turn out not to be negative enough. I tell my father's story of the gambler who lost regularly. One day he heard about a race with only one horse in it, so he bet the rent money. Halfway around the track the horse jumped over the fence and ran away. Invariably things can get worse than people expect. Maybe "worse case" means "the worst we have seen in the past". But it doesn't mean things can't be worse in the future."

Disclosure: The examples of SS Tarapore and Rajeev Malik were pointed out by the Firstpost editor R Jagannathan in an earlier piece. You can read it here)

(Vivek Kaul is a writer. He tweets @kaul_vivek)

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